@INPROCEEDINGS{1257Pätzold2010,
	AUTHOR = {Michael Pätzold and Rubén Heras Evangelio and Thomas Sikora},
	TITLE = {Counting people in crowded environments by fusion of shape and motion information},
	BOOKTITLE = {Proceedings of the IEEE International Conference on Advanced Video and Signal Based Surveillance, PETS 2010 Workshop},
	YEAR = {2010},
	MONTH = aug,
	EDITOR = {IEEE Computer Society},
	PAGES = {157--164},
	ORGANIZATION = {IEEE},
	ADDRESS = {Boston, USA},
	NOTE = {ISBN: 978-0-7695-4264-5},
	DOI = {10.1109/AVSS.2010.92},
	ABSTRACT = {Knowing the number of people in a crowded scene is of big interest in the surveillance scene. In the past, this problem has been tackled mostly in an indirect, statistical way. This paper presents a direct, counting by detection,  method based on fusing spatial information received from an adapted Histogram of Oriented Gradients algorithm (HOG) with temporal information by exploiting distinctive motion characteristics of different human body parts. For that purpose, this paper defines a measure for uniformity of motion. Furthermore, the system performance is enhanced by validating the resulting human hypotheses by tracking and applying a coherent motion detection. The approach is illustrated with an experimental evaluation.}
}